This thesis reports on the development of a novel mass spectrometer combining image charge detection with surface induced dissociation for real-time analysis of intact viruses. Protonated viruses produced using electrospray are accelerated and subsequently impact on a solid surface. Capsid peptides released during the impact are analyzed using time-of-flight mass spectrometry. Image charge detection is used to measure the mass and charge states of structurally intact, electrosprayed viruses prior to impact. Since virus capsids are composed of loosely-bound proteins, collision of viruses with surfaces at moderate impact energies could release intact proteins. The masses and numbers of different protein types combined with the mass of the intact virus represent a unique signature useful for accurate, real-time virus identification. The progress of instrumentation developed thus far is reported. Techniques were developed for electrospraying intact viruses, including electrospray capillaries with small tips and methods for achieving complete desolvation. Significant reduction of low-frequency and other noise was achieved in the image charge detector as well as determination of accurate methods for mass and charge measurement. Improved focusing and transmission efficiency was achieved via an aerodynamic lens. Suitable surfaces were also obtained including conductive diamond and fluorinated self-assembled monolayer (SAM) surfaces.

Image-charge detection is emerging as an important tool to analyze heavy and heterogeneous samples because of its unique advantages in measuring highly charged microparticles. Conventional image-charge detection instruments include at least three fundamental components: an ionization source, an aerodynamic particle delivery system, and an image-charge detector. Here I report research efforts that investigated the mechanisms of image-charge detection and proposed some instrumental developments of these components to suit specific research purposes. In Chapter 2, I report an investigation of the electrospray ionization (ESI) mechanism based on an observation that a certain portion of charged particles generated with an ESI source carried charges opposite to the needle which is biased with a high voltage. Both biological and non-biological samples were used to shed a light on the complex process of droplet evolution in ESI. In Chapter 3, I present two novel designs of printed circuit board (PCB) based image-charge detectors. With these detectors, not only the charge and velocity of each microparticle were investigated, but also the two dimensional trajectories, with applications in aerosolized particle beam diagnostics. Chapter 4 shows several designs of the microparticle delivering system aiming to achieve a faster acceleration of sample microparticles. Finally, Chapter 5 presents some thoughts on future directions for these projects.

Image charge detection is a non-perturbative pre-detection approach for deterministic ion implantation. Using low energy ion bunches as a model system for highly charged single ions, we experimentally studied the error and detection rates of an image charge detector setup. The probability density functions of the signal amplitudes in the Fourier spectrum can be modelled with a generalised gamma distribution to predict error and detection rates. It is shown that the false positive error rate can be minimised at the cost of detection rate, but this does not impair the fidelity of a deterministic implantation process. Independent of the ion species, at a signal to-noise ratio of 2, a false positive error rate of 0.1% is achieved, while the detection rate is about 22%

Image charge detection is presented as a possible candidate to realise deterministic ion implantation. The deterministic placement of single impurities in solid substrates will enable a variety of novel applications, using their quantum mechanical properties for sensors or qubit registers. In this work, experimental techniques are used together with theoretical calculations to develop, characterise and optimise the detection of charged objects in a single pass through an image charge detector. In the main experimental part, ion bunches are employed as a model system for highly charged ions in proof-of-principle measurements with detector prototypes built in our labs. Image charge signals are characterised in the time and frequency domain. Using a statistical measurement and data analysis protocol, the noise and signal probability density functions are determined to calculate error and detection rates. It was found that even at an extremely low signal-to-noise ratio of 2, error rates can be suppressed effectively for high fidelity implantation. Aiming to improve the sensitivity, the maximum possible signal-to-noise ratio is calculated and discussed in dependence on the design parameters of an optimised image charge detector and the kinetic ion parameters. Lastly, a new ion implantation set-up combining focused ion beam technology with a source able to produce highly charged ions is introduced.